What is the null hypothesis in the context of a quality control chart for investment skill?

In the context of a quality control chart for investment skill, the null hypothesis is typically framed in a way that reflects a lack of effectiveness or value added by the investment manager. The correct response states that the manager is not adding value through management. This position serves as the baseline assertion that will be tested against actual performance data.

Quality control charts are used to monitor processes over time and to determine if variations in performance are within acceptable limits or if they indicate significant deviations from the norm. In the realm of investment performance, the null hypothesis represents the assumption that an active manager's results are not superior to a passive strategy or benchmark. By starting with this hypothesis, analysts can employ statistical tests to determine if the manager indeed demonstrates skill by delivering consistent alpha or outperforming a benchmark.

If empirical data suggests that the manager's performance is statistically significantly better than what would be expected under the null hypothesis, then one may reject the null hypothesis and conclude that the manager does have skill and is adding value. This approach is foundational in evaluating investment strategies and understanding the effectiveness of active management within a portfolio.